A compact real-time vision system using integrated memory array processor architecture

Describes a parallel-processor LSI chip (the Integrated Memory Array Processor, IMAP) and a compact real-time vision system (RVS-2). The IMAP integrates 64 8-bit processors, which operate in a SIMD manner, and 2-Mbit image memory on a single chip, and has peak performance of 3.84 GIPS. The RVS-2 consists of 8 IMAPs, a video interface, a control LSI chip (the Real-time Vision System Controller, RVSC) and a host workstation. RVSC is a 16-bit processor which carries out global data operations as well as providing an instruction stream to IMAP processors. In the RVS-2 system, the IMAP processors accomplish data-parallel operations, the RVSC applies global data operations to the results, and the host workstation carries out higher-level recognition tasks using the results obtained by the IMAPs and the RVSC. The peak performance of the RVS-2 is 30 GIPS and most of the basic image processing is carried out in 0.1 to 0.7 ms, which is 50 to 300 times faster the video rate.

Implementation of a real-time image visualization system on a reconfigurable chip (FPGA) is proposed. The system utilizes an innovative stereoscopic image capture, processing and visualization technique. Implementation is done as a two stage process. In the first stage, the stereo pair is captured using two image sensors. The captured images are then synchronized and sent to the second stage for fusion. A controller module is developed, designed, and placed on the FPGA for this purpose. The second stage is used for reconstruction and visualization of the 3D image. An innovative technique employing dual-processor architecture on the same single FPGA is developed for this purpose. The whole system is placed on a single PCB resulting in a fast processing time and the ability to view 3D video in real-time. The system is simulated, implemented, and tested on real images. Results show that this system is a low cost solution for efficient 3D video visualization using a single chip.

Reconfigurable architectures for parallel execution of image processing tasks

The worldwide popularity of playing practices has led to a growing research interest in games’ impact on behavior and cognition. Many studies have already reported the benefits of both video games and board games for cognitive functions. However, these studies have mainly defined the term players according to a minimum play time or in connection to a specific game genre. No study has confronted the cognitive implications of video games and board games in the same statistical model. Thus, it remains unclear whether the cognitive benefits of play are due to play time or game type. To address this issue, in this study, we conducted an online experiment in which 496 participants completed six cognitive tests and a playing practice questionnaire. We examined the between the participants’ overall video game and board game play times and cognitive abilities. The results demonstrated significant relations between overall play time and all cognitive functions. Importantly, video games significantly predicted mental flexibility, planning, visual working memory, visuospatial processing, fluid intelligence, and verbal working memory performance, while board games were not found to predict any cognitive performance. These findings suggest that video games affect cognitive functions in specific ways compared to board games. We encourage further investigation to consider players’ individual differences through their play time and the specific features of the games they play.

The paper is devoted to the problem of formalization of software-hardware solutions in designing real-time computer vision systems. The main attention is paid to the methods of implementation of low-level operations that find features (simple elements) in the image input to the system. Algorithmic types of detectors of simple elements in images are analyzed from the point of view of hardware organization in computer vision systems. In this connection, the necessary performance and memory resources are estimated. The capabilities of parallel and pipeline execution of detector algorithms are investigated. A method of using a field programmable gate array and a digital signal processor in solving the problem of image processing in real-time computer vision systems is considered in detail.

Programming a Pipelined Image Processor

The retina is responsible of the treatment of visual information at early stages. Visual stimuli generate patterns of activity that are transmitted through its layered structure up to the ganglion cells that interface it to the optical nerve. In this trip of micrometers, information is sustained by continuous signals that interact in excitatory and inhibitory ways. This low-level processing compresses the relevant information of the images to a manageable size. The behavior of the more external layers of the biological retina has been successfully modelled within the Cellular Neural Network framework. Interactions between cells are realized on a local basic. Each cell interacts with its nearest neighbors and every cell in the same layer follows the same interconnection pattern. Intra- and inter-layer interactions are continuous in magnitude and time. The evolution of the network can be described by a set of coupled nonlinear differential equations. A mixed-signal VLSI implementation of focal-plane low-level image processing based upon this biological model constitutes a feasible and cost effective alternative to conventional digital processing in real-time applications. A CMOS Programmable Array Processor prototype chip has been designed and fabricated in a standard technology. It has been successfully tested, validating the proposed design techniques. The integrated system consists of a network of 2 coupled layers, containing 32×32 elementary processors, running at different time constants. Involved image processing algorithms can be programmed on this chip by tuning the appropriate interconnection weights, internally coded as analog but programmed via a digital interface. Propagative, active wave phenomena and retina-lake effects can be observed in this chip. Low-level image processing tasks for early vision applications can be developed based on these high-order dynamics.

Video frame interpolation using deep cascaded network structure

There has been significant advances in the field of image and video processing over the past few decades. The term "image processing" is used to describe multiple signal-processing methodologies where images (such as video or picture frames) serves as the input, resulting to another image or a collection of image-related parameters or features. The majority of methodologies to image processing include reducing the picture to a two-dimensional signal and processing it in the same way as any other signal. The term "video processing" on the other hand is used to describe a particular type of signal processing where video files or video streams are utilized as output or input signals. Video recorders, televisions, video codecs, digital versatile, disc players, and other devices all utilize video processing algorithms. This paper provides a survey of the components of Digital Image Processing (DIP) as well as the recent developments in Image Processing technology and DIP applications.

There has been significant advances in the field of image and video processing over the past few decades. The term "image processing" is used to describe multiple signal-processing methodologies where images (such as video or picture frames) serves as the input, resulting to another image or a collection of image-related parameters or features. The majority of methodologies to image processing include reducing the picture to a two-dimensional signal and processing it in the same way as any other signal. The term "video processing" on the other hand is used to describe a particular type of signal processing where video files or video streams are utilized as output or input signals. Video recorders, televisions, video codecs, digital versatile, disc players, and other devices all utilize video processing algorithms. This paper provides a survey of the components of Digital Image Processing (DIP) as well as the recent developments in Image Processing technology and DIP applications.

Development of real-time visual monitoring system for vibration effects on fresh concrete

This paper presents a real-time Visual Content Description System (VCDS) based on MPEG-7 descriptors. In our approach the system's structure is divided into two parts, the first of which is the extraction of the descriptors using the VCDS. The second part uses the descriptors' values in a particular search algorithm. We propose here original solutions for both parts. The proposed system architecture could be used for real-time video indexing and retrieval, content summarization, content delivery, surveillance, personalized services, etc. The descriptor extractor IP core, which is part of the VCDS, implements four MPEG-7 visual descriptors and was designed for ASIC implementation in CMOS 0.35 μm, which is a novel solution for a real-time content description problem. The proposed hardware architecture splits the computational burden into several threads, so that calculations are made simultaneously in order to improve the system's speed. These methods make the hardware implementation of the most computationally demanding modules of the system more time- and power-efficient. Four different variations of the basic hardware architecture are discussed. New search algorithms based on the VCDS responses are also proposed. Experimental results demonstrate the effectiveness of the hardware architectures, and the new approach to similarity-based searching methods.

Visualization is very useful for the study of the heart, but it is still a challenging work to display the detailed heart because of the complex structure and expensive computation. Very few systems have been developed to satisfy this work specially. In this paper, we designed and implemented a GPU-based and real-time cardiac visualization system (GRCVS). The illumination model and the context-preserving model are integrated into the system, so that it can generate better images and preserve the important boundary information at the same time. The rendering process is programmed with CUDA, which helps to view the final image in real time. The system also provides strong interactive ability: it supplies visual and concise interfaces to set various parameters which are used to adjust image effect and user can also use simple ways to observe the images quickly and conveniently. The system has been proved to be valuable for the study of the heart in biomedical field.

Hand-eye relation in visual servoing involves eye-in-hand and eye-to-hand configuration. Both have its own merit and drawback regarding to its precision and sight range. This paper addresses this problem and introduces the camera utilization as eye-to-hand configuration for the second robot, while it retains as eye-in-hand for the first robot. Hence, the camera becomes mobile and provides more precision and more global sight of scene. Moreover, this paper also addresses the real-time constraints within real-time vision system and real-time data exchange due to different processing units for robot and vision system. Here, a pattern design and simplified image processing are considered. This paper considers a 3D visual servoing within dynamic look and move scheme based on object pose. The system performance is validated by the experimental result.

Knowledge of the microcirculatory system has added significant value to the analysis of tissue oxygenation and perfusion. While developments in videomicroscopy technology have enabled medical researchers and physicians to observe the microvascular system, the available software tools are limited in their capabilities to determine quantitative features of microcirculation, either automatically or accurately. In particular, microvessel density has been a critical diagnostic measure in evaluating disease progression and a prognostic indicator in various clinical conditions. As a result, automated analysis of the microcirculatory system can be substantially beneficial in various real-time and off-line therapeutic medical applications, such as optimization of resuscitation. This study focuses on the development of an algorithm to automatically segment microvessels, calculate the density of capillaries in microcirculatory videos, and determine the distribution of blood circulation. The proposed technique is divided into four major steps: video stabilization, video enhancement, segmentation and post-processing. The stabilization step estimates motion and corrects for the motion artifacts using an appropriate motion model. Video enhancement improves the visual quality of video frames through preprocessing, vessel enhancement and edge enhancement. The resulting frames are combined through an adjusted weighted median filter and the resulting frame is then thresholded using an entropic thresholding technique. Finally, a region growing technique is utilized to correct for the discontinuity of blood vessels. Using the final binary results, the most commonly used measure for the assessment of microcirculation, i.e. Functional Capillary Density (FCD), is calculated. The designed technique is applied to video recordings of healthy and diseased human and animal samples obtained by MicroScan device based on Sidestream Dark Field (SDF) imaging modality. To validate the final results, the calculated FCD results are compared with the results obtained by blind detailed inspection of three medical experts, who have used AVA (Automated Vascular Analysis) semi-automated microcirculation analysis software. Since there is neither a fully automated accurate microcirculation analysis program, nor a publicly available annotated database of microcirculation videos, the results acquired by the experts are considered the gold standard. Bland-Altman plots show that there is Good Agreement between the results of the algorithm and that of gold standard. In summary, the main objective of this study is to eliminate the need for human interaction to edit/ correct results, to improve the accuracy of stabilization and segmentation, and to reduce the overall computation time. The proposed methodology impacts the field of computer science through development of image processing techniques to discover the knowledge in grayscale video frames. The broad impact of this work is to assist physicians, medical researchers and caregivers in making diagnostic and therapeutic decisions for microcirculatory abnormalities and in studying of the human microcirculation.